api_client.py

#!/usr/bin/env python3
"""
Simple client script to test the AI Text Humanizer API
"""

import requests
import json
import time

# Configuration
API_BASE_URL = "http://localhost:8000"

def test_api_connection():
    """Test if the API server is running"""
    try:
        response = requests.get(f"{API_BASE_URL}/health", timeout=5)
        if response.status_code == 200:
            print("✅ API server is running!")
            return True
        else:
            print(f"❌ API server responded with status {response.status_code}")
            return False
    except requests.exceptions.RequestException as e:
        print(f"❌ Cannot connect to API server: {e}")
        print("💡 Make sure to run: python fastapi_server.py")
        return False

def humanize_single_text(text, style="natural", intensity=0.7):
    """Humanize a single piece of text"""
    try:
        payload = {
            "text": text,
            "style": style,
            "intensity": intensity
        }
        
        response = requests.post(
            f"{API_BASE_URL}/humanize",
            json=payload,
            headers={"Content-Type": "application/json"}
        )
        
        if response.status_code == 200:
            return response.json()
        else:
            print(f"❌ API Error: {response.status_code}")
            print(response.text)
            return None
            
    except requests.exceptions.RequestException as e:
        print(f"❌ Request failed: {e}")
        return None

def humanize_batch_texts(texts, style="natural", intensity=0.7):
    """Humanize multiple texts in batch"""
    try:
        payload = {
            "texts": texts,
            "style": style,
            "intensity": intensity
        }
        
        response = requests.post(
            f"{API_BASE_URL}/batch_humanize",
            json=payload,
            headers={"Content-Type": "application/json"}
        )
        
        if response.status_code == 200:
            return response.json()
        else:
            print(f"❌ API Error: {response.status_code}")
            print(response.text)
            return None
            
    except requests.exceptions.RequestException as e:
        print(f"❌ Request failed: {e}")
        return None

def display_result(result):
    """Display humanization result in a formatted way"""
    if not result:
        return
        
    print("\n" + "="*60)
    print("📝 ORIGINAL TEXT:")
    print("-" * 40)
    print(result['original_text'])
    
    print("\n✨ HUMANIZED TEXT:")
    print("-" * 40)
    print(result['humanized_text'])
    
    print(f"\n📊 STATS:")
    print(f"   • Similarity Score: {result['similarity_score']:.3f}")
    print(f"   • Processing Time: {result['processing_time_ms']:.1f}ms")
    print(f"   • Style: {result['style'].title()}")
    print(f"   • Intensity: {result['intensity']}")
    
    if result['changes_made']:
        print(f"\n🔄 CHANGES MADE:")
        for change in result['changes_made']:
            print(f"   • {change}")
    else:
        print(f"\n🔄 CHANGES MADE: None")

def interactive_mode():
    """Interactive mode for testing"""
    print("\n🎯 Interactive Mode")
    print("Type 'quit' to exit\n")
    
    while True:
        text = input("📝 Enter text to humanize: ").strip()
        
        if text.lower() in ['quit', 'exit', 'q']:
            print("👋 Goodbye!")
            break
            
        if not text:
            print("⚠️ Please enter some text.")
            continue
        
        # Get style preference
        print("\n🎨 Choose style:")
        print("1. Natural")
        print("2. Casual") 
        print("3. Conversational")
        
        style_choice = input("Enter choice (1-3) or press Enter for Natural: ").strip()
        style_map = {'1': 'natural', '2': 'casual', '3': 'conversational'}
        style = style_map.get(style_choice, 'natural')
        
        # Get intensity
        intensity_input = input("⚡ Enter intensity (0.1-1.0) or press Enter for 0.7: ").strip()
        try:
            intensity = float(intensity_input) if intensity_input else 0.7
            intensity = max(0.1, min(1.0, intensity))  # Clamp between 0.1 and 1.0
        except ValueError:
            intensity = 0.7
        
        print(f"\n🚀 Processing with {style} style, intensity {intensity}...")
        
        result = humanize_single_text(text, style, intensity)
        display_result(result)
        
        print("\n" + "-"*60 + "\n")

def run_examples():
    """Run example demonstrations"""
    print("\n🎯 Running Example Tests")
    print("=" * 50)
    
    examples = [
        {
            "text": "Furthermore, it is important to note that artificial intelligence systems demonstrate significant capabilities in natural language processing tasks. Subsequently, these systems can analyze and generate text with remarkable accuracy.",
            "style": "conversational",
            "intensity": 0.8,
            "description": "AI-formal text → Conversational"
        },
        {
            "text": "The implementation of this comprehensive solution will facilitate the optimization of business processes and operational workflows. Moreover, it will demonstrate substantial improvements in efficiency metrics.",
            "style": "natural",
            "intensity": 0.6,
            "description": "Business text → Natural"
        },
        {
            "text": "In conclusion, the systematic analysis reveals that the proposed methodology demonstrates significant potential for enhancing performance indicators.",
            "style": "casual",
            "intensity": 0.7,
            "description": "Academic text → Casual"
        }
    ]
    
    for i, example in enumerate(examples, 1):
        print(f"\n🔬 Example {i}: {example['description']}")
        print("-" * 50)
        
        result = humanize_single_text(
            text=example['text'],
            style=example['style'],
            intensity=example['intensity']
        )
        
        display_result(result)
        
        # Small delay between examples
        time.sleep(1)

def test_batch_processing():
    """Test batch processing functionality"""
    print("\n🔄 Testing Batch Processing")
    print("=" * 50)
    
    texts = [
        "Furthermore, the comprehensive analysis demonstrates significant improvements.",
        "Subsequently, the implementation will facilitate optimization of processes.",
        "Therefore, it is essential to utilize these methodologies effectively."
    ]
    
    print(f"📦 Processing {len(texts)} texts in batch...")
    
    start_time = time.time()
    result = humanize_batch_texts(texts, style="casual", intensity=0.7)
    total_time = time.time() - start_time
    
    if result:
        print(f"\n✅ Batch processing completed in {total_time:.1f}s")
        print(f"⚡ Total API time: {result['total_processing_time_ms']:.1f}ms")
        
        for i, text_result in enumerate(result['results'], 1):
            print(f"\n📝 Text {i}:")
            print(f"   Original: {text_result['original_text'][:50]}...")
            print(f"   Humanized: {text_result['humanized_text'][:50]}...")
            print(f"   Similarity: {text_result['similarity_score']:.3f}")

def main():
    """Main function"""
    print("🤖➡️👤 AI Text Humanizer - API Client")
    print("=" * 50)
    
    # Test API connection
    if not test_api_connection():
        return
    
    while True:
        print("\n🎯 Choose an option:")
        print("1. Run example demonstrations")
        print("2. Test batch processing") 
        print("3. Interactive mode")
        print("4. Exit")
        
        choice = input("\nEnter your choice (1-4): ").strip()
        
        if choice == '1':
            run_examples()
        elif choice == '2':
            test_batch_processing()
        elif choice == '3':
            interactive_mode()
        elif choice == '4':
            print("\n👋 Thanks for using AI Text Humanizer!")
            break
        else:
            print("❌ Invalid choice. Please enter 1, 2, 3, or 4.")

if __name__ == "__main__":
    main()